AP Statistics Audit Syllabus COURSE DESCRIPTION: AP Statistics is the high school equivalent of a one semester, introductory college statistics course. In this course, students develop strategies for collecting, organizing, analyzing, and drawing conclusions from data. Students design, administer, and tabulate results from surveys and experiments. Probability and simulations aid students in constructing models for chance behavior. Sampling distributions provide the logical structure for confidence intervals and hypothesis tests. Students use a TI 8/8 graphing calculator, Fathom, and Minitab statistical software, and Web based java applets to investigate statistical concepts. To develop effective statistical communication skills, students are required to prepare frequent written and oral analyses of real data. COURSE GOALS: In AP Statistics, students are expected to learn Skills To produce convincing oral and written statistical arguments, using appropriate terminology, in a variety of applied settings. When and how to use technology to aid them in solving statistical problems Knowledge Essential techniques for producing data (surveys, experiments, observational studies), analyzing data (graphical & numerical summaries), modeling data (probability, random variables, sampling distributions), and drawing conclusions from data (inference procedures confidence intervals and significance tests) Habits of mind To become critical consumers of published statistical results by heightening their awareness of ways in which statistics can be improperly used to mislead, confuse, or distort the truth. COURSE OUTLINE: Text: The Practice of Statistics ( th edition), by Starnes, Tabor, Yates, and Moore, W. H. Freeman & Co., 0.
FIRST NINE WEEKS Chapter Designing Studies (7 days) Day Topics Learning Objectives Students will be able to 6. Introduction, The Idea of a Sample Survey, How to Sample Badly, How to Sample Well: Simple Random Sampling, Other Random Sampling Methods. Inference for Sampling, Sample Surveys: What Can Go Wrong?. Observational Study versus Experiment, The Language of Experiments. How to Experiment Badly, How to Experiment Well, Completely Randomized Designs. Experiments: What Can Go Wrong? Inference for Experiments, Blocking. Scope of Inference, The Challenges of Establishing Causation, Data Ethics Chapter /Free Response AP Problem 7 Chapter Test Identify the population and sample in a statistical study. Identify voluntary response samples and convenience samples. Explain how these sampling methods can lead to bias. Describe how to obtain a random sample using slips of paper, technology, or a table of random digits. Distinguish a simple random sample from a stratified random sample or cluster sample. Give the advantages and disadvantages of each sampling method. Explain how undercoverage, nonresponse, question wording, and other aspects of a sample survey can lead to bias. Distinguish between an observational study and an experiment. Explain the concept of confounding and how it limits the ability to make cause and effect conclusions. Identify the experimental units, explanatory and response variables, and treatments. Explain the purpose of comparison, random, control, and replication in an experiment. Describe a completely randomized design for an experiment, including how to randomly assign treatments using slips of paper, technology, or a table of random digits. Describe the placebo effect and the purpose of blinding in an experiment. Interpret the meaning of statistically significant in the context of an experiment. Explain the purpose of blocking in an experiment. Describe a randomized block design or a matched pairs design for an experiment. Describe the scope of inference that is appropriate in a statistical study. Evaluate whether a statistical study has been carried out in an ethical manner.,,, 7, 9,,, 7, 9,,, 7, 9,,,, 7,, 7, 9,,, 7, 9, 6, 6, 6 67, 69, 7, 7, 7, 77, 79, 8, 8 8, 87 9, 97 0, Chapter Chapter AP Practice Exam Chapter Project: Students work in teams of to design and carry out an experiment to investigate response bias, write a summary report, and give a 0 minute oral synopsis to their classmates. See rubric on page.
Chapter Exploring Data (6 Days) Day Topics Learning Objectives Students will be able to Chapter Introduction. Bar Graphs and Pie Charts, Graphs: Good and Bad. Two Way Tables and Marginal Distributions, Relationships between Categorical Variables: Conditional Distributions. Dotplots, Describing Shape, Comparing Distributions, Stemplots, Histograms, Using Histograms Wisely. Measuring Center: Mean and Median, Comparing the Mean and Median, Measuring Spread: Range and IQR, Identifying Outliers, Five Number Summary and Boxplots,. Measuring Spread: Standard Deviation, Choosing Measures of Center and Spread, Organizing a Statistics Problem Chapter /Free Response AP Problem 6 Chapter Test Identify the individuals and variables in a set of data. Classify variables as categorical or quantitative. Display categorical data with a bar graph. Decide if it would be appropriate to make a pie chart. Identify what makes some graphs of categorical data deceptive. Calculate and display the marginal distribution of a categorical variable from a two way table. Calculate and display the conditional distribution of a categorical variable for a particular value of the other categorical variable in a two way table. Describe the association between two categorical variables by comparing appropriate conditional distributions. Make and interpret dotplots and stemplots of quantitative data. Describe the overall pattern (shape, center, and spread) of a distribution and identify any major departures from the pattern (outliers). Identify the shape of a distribution from a graph as roughly symmetric or skewed. Compare distributions of quantitative data using dotplots or stemplots. Make and interpret histograms of quantitative data. Compare distributions of quantitative data using histograms. Calculate measures of center (mean, median). Calculate and interpret measures of spread (range, IQR). Choose the most appropriate measure of center and spread in a given setting. Identify outliers using the. IQR rule. Make and interpret boxplots of quantitative data. Calculate and interpret measures of spread (standard deviation). Choose the most appropriate measure of center and spread in a given setting. Use appropriate graphs and numerical summaries to compare distributions of quantitative variables.,,, 7, 8,,,, 7 9,,,, 7 7, 9,,,, 7,,, 9, 60, 6, 69 7 79, 8, 8, 87, 89, 9, 9, 9, 97, 99, 0, 0, 07 0 Chapter
Chapter Modeling Distribution of Data (6 Days) Day Topics Learning Objectives Students will be able to. Measuring Position: Percentiles; Cumulative Relative Frequency Graphs; Measuring Position: z scores. Transforming Data. Density Curves, The 68 9 99.7 Rule; The Standard Normal Distribution. Normal Distribution Calculations, Assessing Normality Chapter /Free Response AP Problem 6 Chapter Test Find and interpret the percentile of an individual value within a distribution of data. Estimate percentiles and individual values using a cumulative relative frequency graph. Find and interpret the standardized score ( z score) of an individual value within a distribution of data. Describe the effect of adding, subtracting, multiplying by, or dividing by a constant on the shape, center, and spread of a distribution of data. Estimate the relative locations of the median and mean on a density curve. Use the 68 9 99.7 rule to estimate areas (proportions of values) in a Normal distribution. Use Table A or technology to find (i) the proportion of z values in a specified interval, or (ii) a z score from a percentile in the standard Normal distribution. Use Table A or technology to find (i) the proportion of values in a specified interval, or (ii) the value that corresponds to a given percentile in any Normal distribution. Determine if a distribution of data is approximately Normal from graphical and numerical evidence.,,, 9,,, 7, 9,,, 0,, 9,,,, 7, 9,,, 7, 9,, 6, 6, 66, 67, 69 7 Chapter Cumulative AP Practice Exam :,,,, 6, 8, 0
Chapter Probability: What are the Chances? (7 Days) Day Topics Learning Objectives Students will be able to 6. The Idea of Probability, Myths about Randomness, Simulation. Probability Models, Basic Rules of Probability. Two Way Tables, Probability, and the General Addition Rule, Venn Diagrams and Probability. What Is Conditional Probability?, The General Multiplication Rule and Tree Diagrams,. Conditional Probability and Independence: A Special Multiplication Rule Chapter /Free Response AP Problem 7 Chapter Test Interpret probability as a long run relative frequency. Use simulation to model chance behavior. Determine a probability model for a chance process. Use basic probability rules, including the complement rule and the addition rule for mutually exclusive events. Use a two way table or Venn diagram to model a chance process and calculate probabilities involving two events. Use the general addition rule to calculate probabilities. Calculate and interpret conditional probabilities. Use the general multiplication rule to calculate probabilities. Use tree diagrams to model a chance process and calculate probabilities involving two or more events. Determine whether two events are independent. When appropriate, use the multiplication rule for independent events to compute probabilities.,, 7, 9,,, 7, 9,, 7,,, 9,,,, 7 9, 6, 9,,, 7 60, 6, 6, 67, 7, 7, 77, 79 8, 8, 8, 89, 9, 9, 9, 97 99 Chapter
Chapter 6 Random Variables (6 Days) Day Topics Learning Objectives Students will be able to Chapter 6 Introduction, 6. Discrete Random Variables, Mean (Expected Value) of a Discrete Random Variable, Standard Deviation (and Variance) of a Discrete Random Variable, Continuous Random Variables 6. Linear Transformations, Combining Random Variables, Combining Normal Random Variables 6. Binomial Settings and Binomial Random Variables, Binomial Probabilities 6. Mean and Standard Deviation of a Binomial Distribution, Binomial Distributions in Statistical Sampling, Geometric Random Variables Chapter 6 /Free Response AP Problem! 6 Chapter 6 Test Compute probabilities using the probability distribution of a discrete random variable. Calculate and interpret the mean (expected value) of a discrete random variable. Calculate and interpret the standard deviation of a discrete random variable. Compute probabilities using the probability distribution of a continuous random variable. Describe the effects of transforming a random variable by adding or subtracting a constant and multiplying or dividing by a constant. Find the mean and standard deviation of the sum or difference of independent random variables. Find probabilities involving the sum or difference of independent Normal random variables. Determine whether the conditions for using a binomial random variable are met. Compute and interpret probabilities involving binomial distributions. Calculate the mean and standard deviation of a binomial random variable. Interpret these values in context. Find probabilities involving geometric random variables.,,, 7, 9,,,,, 7, 8,,, 7 0,, 7, 9,,, 7, 9,,,, 7 9, 6 6, 6, 66, 69, 7, 7, 7, 77 79, 8, 8, 8, 87, 89, 9, 9, 97, 99, 0 0 Chapter 6 6
Chapter 7 Sampling Distributions (7 Days) Day Topics Learning Objectives Students will be able to 6 Introduction: German Tank Problem, 7. Parameters and Statistics, Sampling Variability, Describing Sampling Distributions 7. The Sampling Distribution of, Using the Normal Approximation for. 7. The Sampling Distribution of : Mean and Standard Deviation, Sampling from a Normal Population 7. The Central Limit Theorem Chapter 7 /Free Response AP Problem! 7 Chapter 7 Test Distinguish between a parameter and a statistic. Distinguish among the distribution of a population, the distribution of a sample, and the sampling distribution of a statistic. Use the sampling distribution of a statistic to evaluate a claim about a parameter. Determine whether or not a statistic is an unbiased estimator of a population parameter. Describe the relationship between sample size and the variability of a statistic. Find the mean and standard deviation of the sampling distribution of a sample proportion 0% condition before calculating.. Check the Determine if the sampling distribution of is approximately Normal. If appropriate, use a Normal distribution to calculate probabilities involving. Find the mean and standard deviation of the sampling distribution of a sample mean. Check the 0% condition before calculating. If appropriate, use a Normal distribution to calculate probabilities involving. Explain how the shape of the sampling distribution of is affected by the shape of the population distribution and the sample size. If appropriate, use a Normal distribution to calculate probabilities involving.,,, 7, 9,,,, 7, 9, 7, 9,,, 7, 9 6, 9,,, 7, 9, 6, 6, 6 68 Chapter 7 Cumulative AP Practice Exam 7
Chapter 8 Estimating with Confidence (7 Days) Day Topics Learning objectives Students will be able to 6 Chapter 8 Introduction; 8. The Idea of a Confidence Interval, Interpreting Confidence Intervals and Confidence Levels 8. Constructing a Confidence Interval; Using Confidence Intervals Wisely 8. Conditions for Estimating p, Constructing a Confidence Interval for p, Putting It All Together: The Four Step Process, Choosing the Sample Size 8. The Problem of unknown, When Is Unknown: The t Distributions, Conditions for Estimating 8. Constructing a Confidence Interval for, Choosing a Sample Size Chapter 8 /Free Response AP Problem! 7 Chapter 8 Test Interpret a confidence interval in context. Interpret a confidence level in context. Determine the point estimate and margin of error from a confidence interval. Describe how the sample size and confidence level affect the length of a confidence interval. Explain how practical issues like nonresponse, undercoverage, and response bias can affect the interpretation of a confidence interval. State and check the Random, 0%, and Large Counts conditions for constructing a confidence interval for a population proportion. Determine critical values for calculating a C% confidence interval for a population proportion using a table or technology. Construct and interpret a confidence interval for a population proportion. Determine the sample size required to obtain a C% confidence interval for a population proportion with a specified margin of error. Explain how the t distributions are different from the standard Normal distribution and why it is necessary to use a t distribution when calculating a confidence interval for a population mean. Determine critical values for calculating a C% confidence interval for a population mean using a table or technology. State and check the Random, 0%, and Normal/Large Sample conditions for constructing a confidence interval for a population mean. Construct and interpret a confidence interval for a population mean. Determine the sample size required to obtain a C% confidence interval for a population mean with a specified margin of error.,,, 7, 9 0,,,, 7, 9 0,,,, 7, 9,,,, 7 9,, 7, 9 6, 6, 69, 7, 7, 7 78 Chapter 8 8
Chapter 9 Testing a Claim (8 Days) Day Topics Learning Objectives Students will be able to 9. Stating Hypotheses, The Reasoning of Significance Tests, Interpreting P values, Statistical Significance 9. Type I and Type II Errors 6 7 9. Carrying Out a Significance Test, The One Sample z Test for a Proportion 9. Two Sided Tests, Why Confidence Intervals Give More Information, Type II Error and the Power of a Test 9. Carrying Out a Significance Test for, The One Sample t Test, Two Sided Tests and Confidence Intervals 9. Inference for Means: Paired Data, Using Tests Wisely Chapter 9 /Free Response AP Problem! 8 Chapter 9 Test State the null and alternative hypotheses for a significance test about a population parameter. Interpret a P value in context. Determine if the results of a study are statistically significant and draw an appropriate conclusion using a significance level. Interpret a Type I and a Type II error in context, and give a consequence of each. State and check the Random, 0%, and Large Counts conditions for performing a significance test about a population proportion. Perform a significance test about a population proportion. Use a confidence interval to draw a conclusion for a two sided test about a population parameter. Interpret the power of a test and describe what factors affect the power of a test. Describe the relationship among the probability of a Type I error (significance level), the probability of a Type II error, and the power of a test. State and check the Random, 0%, and Normal/Large Sample conditions for performing a significance test about a population mean. Perform a significance test about a population mean. Use a confidence interval to draw a conclusion for a two sided test about a population parameter. Perform a significance test about a mean difference using paired data.,,, 7, 9,,, 7, 9,, 8,,, 9,,, 7,,,, 7 9 6, 6, 69, 7, 77, 79 8, 8, 87, 89 9, 9, 9 0 Chapter 9 9
SECOND NINE WEEKS Chapter 0 Comparing Two Populations or Groups (8 Days) Day Topics Learning Objectives Students will be able to 6 7 Is Yawning Contagious? Activity, 0. The Sampling Distribution of a Difference between Two Proportions, 0. Confidence Intervals for 0. Significance Tests for Inference for Experiments 0. Does Polyester Decay? Activity, The Sampling Distribution of a Difference between Two Means 0. The Two Sample t Statistic, Confidence Intervals for 0. Significance Tests for, Using Two Sample t Procedures Wisely Chapter 0 / Free Response AP Problem! 8 Chapter 0 Test Describe the shape, center, and spread of the sampling distribution of Determine whether the conditions are met for doing inference about Construct and interpret a confidence interval to compare two proportions. Perform a significance test to compare two proportions. Describe the shape, center, and spread of the sampling distribution of Determine whether the conditions are met for doing inference about Construct and interpret a confidence interval to compare two means. Perform a significance test to compare two means. Determine when it is appropriate to use two sample t procedures versus paired t procedures.,,, 7, 9,,, 7,,,,, 8, 7, 9,,, 7,, 7 60 Chapter 0 Cumulative AP Practice Exam 0
Chapter Describing Relationships ( Days) Day Topics Learning Objectives Students will be able to Chapter Introduction. Explanatory and response variables, displaying relationships: scatterplots, describing scatterplots. Measuring linear association: correlation, facts about correlation. Least squares regression, interpreting a regression line, prediction, residuals, Calculating the equation of the least squares regression line, determining whether a linear model is appropriate: residual plots. How well the line fits the data: the role of s and r in regression, Interpreting computer regression output, regression to the mean, correlation and regression wisdom Chapter /Free Response AP Problem Chapter Test Identify explanatory and response variables in situations where one variable helps to explain or influences the other. Make a scatterplot to display the relationship between two quantitative variables. Describe the direction, form, and strength of a relationship displayed in a scatterplot and recognize outliers in a scatterplot. Interpret the correlation. Understand the basic properties of correlation, including how the correlation is influenced by outliers. Use technology to calculate correlation. Explain why association does not imply causation. Interpret the slope and y intercept of a least squares regression line. Use the least squares regression line to predict y for a given x. Explain the dangers of extrapolation. Calculate and interpret residuals. Explain the concept of least squares. Determine the equation of a least squares regression line using technology. Construct and interpret residual plots to assess if a linear model is appropriate. Interpret the standard deviation of the residuals and and use these values to assess how well the least squares regression line models the relationship between two variables. Determine the equation of a least squares regression line using computer output. Describe how the slope, y intercept, standard deviation of the residuals, and are influenced by outliers. Find the slope and y intercept of the least squares regression line from the means and standard deviations of x and y and their correlation.,, 7,,, 8, 7,, 7, 9,,,, 7, 9, 8, 0,, 8, 9, 6, 6, 6, 69, 7 78 Chapter Cumulative AP Practice Exam :, 7, 9
Chapter Inference for Distributions of Categorical Data ( Days) Day Topics Learning objectives Students will be able to Activity: The Candy Man Can;. Comparing Observed and Expected Counts: The Chi Square Statistic; The Chi Square Distributions and P values, Carrying Out a Test; Follow Up Analysis. Comparing Distributions of a Categorical Variable; Expected Counts and the Chi Square Statistic; The Chi Square Test for Homogeneity. Relationships between Two Categorical Variables; the Chi Square Test for Independence; Using Chi Square Tests Wisely Chapter / Free Response AP Problem! Chapter Test State appropriate hypotheses and compute expected counts for a chi square test for goodness of fit. Calculate the chi square statistic, degrees of freedom, and P value for a chi square test for goodness of fit. Perform a chi square test for goodness of fit. Conduct a follow up analysis when the results of a chi square test are statistically significant. Compare conditional distributions for data in a two way table. State appropriate hypotheses and compute expected counts for a chi square test based on data in a two way table. Calculate the chi square statistic, degrees of freedom, and P value for a chi square test based on data in a two way table. Perform a chi square test for homogeneity. Perform a chi square test for independence. Choose the appropriate chi square test.,,, 7, 9,,, 7 9, 7, 9,,,, 7, 9,,, 7, 9, Chapter
Chapter More about Regression ( Days) Day Topics Learning Objectives Students will be able to Activity: The Helicopter Experiment;. Sampling Distribution of b; Conditions for Regression Inference Check the conditions for performing inference about the slope of the population (true) regression line.,. Estimating the Parameters; Constructing a Confidence Interval for the Slope, Performing a Significance Test for the Slope. Transforming with Powers and Roots, Transforming with Logarithms; Putting it all Together: Which Transformation Should We Choose? Chapter / Free Response AP Problem! Chapter Test Interpret the values of a, b, s,, and in context, and determine these values from computer output. Construct and interpret a confidence interval for the slope line. of the population (true) regression Perform a significance test about the slope of the population (true) regression line. Use transformations involving powers and roots to find a power model that describes the relationship between two variables, and use the model to make predictions. Use transformations involving logarithms to find a power model or an exponential model that describes the relationship between two variables, and use the model to make predictions. Determine which of several transformations does a better job of producing a linear relationship., 7, 9,,,, 7 9,,,, 7, 9,,,, 7 0 Chapter Cumulative AP Practice Test AP EXAM REVIEW ( days) Practice AP Free Response Questions Choosing the Correct Inference Procedure Flashcards Mock Grading Sessions Practice Multiple Choice Questions AP STATISTICS EXAM ( day)
Rubric for Chapter Project Response Bias Project Introduction Data Collection Graphs and Summary Statistics Conclusions Poster, Presentation, & Communication = Complete = Substantial = Developing = Minimal Describes the context of the research Has a clearly stated question of interest Provides a hypothesis about the question of interest Question of interest is of appropriate difficulty Method of data collection is clearly described Includes appropriate randomization Describes efforts to reduce bias, variability, confounding Quantity of data collected is appropriate Raw data is included in a two way table (categorical) or in lists (quantitative) Appropriate graphs are included Graphs are neat, easy to compare, and clearly labeled, including clear identification of treatments Appropriate summary statistics are included in discussion (e.g., percentages for categorical data, means for quantitative data) Uses the results of the study to correctly answer question of interest Discusses what inferences are appropriate based on study design Shows good evidence of critical reflection (discusses possible errors, limitations.) Has a clear, holistic understanding of the project Poster is well organized, neat, and easy to read Poster included pictures of data collection in progress and is visually appealing Oral is well organized Introduces the context of the research and has a specific question of interest Suggests hypothesis OR has appropriate difficulty Method of data collection is clearly described Some effort is made to incorporate principles of good data collection Quantity of data collected is appropriate Appropriate graphs are included Graphs are neat, clearly labeled, and easy to compare Appropriate summary statistics or raw data are included Makes a correct conclusion Discusses what inferences are appropriate or shows good evidence of critical reflection Has a clear, holistic understanding of the project, but poster is unorganized, lacks visual appeal, or oral presentation is not organized Introduces the context of the research and question of interest OR has question of interest and a hypothesis Method of data collection is described Some effort is made to incorporate principles of good data collection Graphs and summary statistics are included Makes a partially correct conclusion Shows some evidence of critical reflection The poster and oral presentation have several problems Briefly describes the context of the research Some evidence of data collection Graphs or summary statistics are included Makes a conclusion Communica tion and organization are poor
After the AP Exam: Final Project (See rubric on page 6) Purpose: The purpose of this project is for you to actually do statistics. You are to formulate a statistical question, design a study to answer the question, conduct the study, collect the data, analyze the data, and use statistical inference to answer the question. You are going to do it all!! Topics: You may do your study on any topic, but you must be able to include all 6 steps listed above. Make it interesting and note that degree of difficulty is part of the grade. Group Size: You may work alone or with a partner for this project. Proposal ( points): To get your project approved, you must be able to demonstrate how your study will meet the requirements of the project. In other words, you need to clearly and completely communicate your statistical question, your explanatory and response variables, the test/interval you will use to analyze the results, and how you will collect the data so the conditions for inference will be satisfied. You must also make sure that your study will be safe and ethical if you are using human subjects. The proposal should be typed. If your proposal isn t approved, you must resubmit the proposal for partial credit until it is approved. Poster (7 points): The key to a good statistical poster is communication and organization. Make sure all components of the poster are focused on answering the question of interest and that statistical vocabulary is used correctly. The poster should include: Title (in the form of a question). Introduction. In the introduction you should discuss what question you are trying to answer, why you chose this topic, what your hypotheses are, and how you will analyze your data. Data Collection. In this section you will describe how you obtained your data. Be specific. Graphs, Summary Statistics and the Raw Data (if numerical). Make sure the graphs are well labeled, easy to compare, and help answer the question of interest. You should include a brief discussion of the graphs and interpretations of the summary statistics. Analysis. In this section, identify the inference procedure you used along with the test statistic and P value and/or confidence interval. Also, discuss how you know that your inference procedure is valid. Conclusion. In this section, you will state your conclusion. You should also discuss any possible errors or limitations to your conclusion, what you could do to improve the study next time, and any other critical reflections. Live action pictures of your data collection in progress. Presentation: You will be required to give a minute oral presentation to the class.
Rubric for Final Project Final Project = Complete = Substantial = Developing = Minimal Introduction Describes the context of the research Has a clearly stated question of interest Clearly defines the parameter of interest and states correct hypotheses (for tests) Question of interest is of appropriate difficulty Introduces the context of the research and has a specific question of interest Has correct parameter/ hypotheses OR has appropriate difficulty Introduces the context of the research and has a specific question of interest OR has question of interest and parameter/ hypotheses Briefly describes the context of the research Data Collection Graphs and Summary Statistics Analysis Conclusions Overall Presentation/ Communicatio n Method of data collection is clearly described Includes appropriate randomization Describes efforts to reduce bias, variability, confounding Quantity of data collected is appropriate Appropriate graphs are included Graphs are neat, clearly labeled, and easy to compare Appropriate summary statistics are included Summary statistics are discussed and correctly interpreted Correct inference procedure is chosen Use of inference procedure is justified Test statistic/ P value or confidence interval is calculated correctly P value or confidence interval is interpreted correctly Uses P value/confidence interval to correctly answer question of interest Discusses what inferences are appropriate based on study design Shows good evidence of critical reflection (discusses possible errors, limitations, alternate explanations, etc.) Clear, holistic understanding of the project Poster is well organized, neat and easy to read Statistical vocabulary is used correctly Poster is visually appealing Method of data collection is clearly described Some effort is made to incorporate principles of good data collection Quantity of data is appropriate Appropriate graphs are included Graphs are neat, clearly labeled, and easy to compare Appropriate summary statistics are included Correct inference procedure is chosen Lacks justification, lacks interpretation, or makes a calculation error Makes a correct conclusion Discusses what inferences are appropriate Shows some evidence of critical reflection Clear, holistic understanding of the project Statistical vocabulary is used correctly Poster is unorganized or isn t visually appealing, Method of data collection is described Some effort is made to incorporate principles of good data collection Graphs and summary statistics are included Correct inference procedure is chosen Test statistic/ P value or confidence interval is calculated correctly Makes a partially correct conclusion (such as accepting null). Shows some evidence of critical reflection Poster is not well done or communication is poor Some evidence of data collection Graphs or summary statistics are included Inference procedure is attempted Makes a conclusion Communication and organization are very poor 6